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Record W2146717266 · doi:10.5539/ass.v10n1p179

Learning Transfer at Skill Institutions’ and Workplace Environment: A Conceptual Framework

2013· article· en· W2146717266 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAsian Social Science · 2013
Typearticle
Languageen
FieldPsychology
TopicHuman Resource Development and Performance Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsKnowledge managementConceptual frameworkTransfer of trainingTransfer of learningThe Conceptual FrameworkKnowledge transferInstitutionWorkplace learningConceptual modelLearning environmentBusinessComputer sciencePsychologyProcess managementPedagogyEngineeringPolitical scienceWork (physics)SociologyArtificial intelligence

Abstract

fetched live from OpenAlex

Efficient human resource management and skills development are central to any organization. However, identified less than 15 to 20 percent of the knowledge and skills acquired in trainings were actually applied in workplaces. Lack of awareness and limited skills learned have caused loss of funds invested in training programs and continued to contribute to mismatches in labour issues. Thus, this conceptual paper proposes key aspects of learning transfer required in training institution based on National Occupational Skill Standards (NOSS) system and in workplace environment. A conceptual framework which is based on critical reviews of current approaches in studies of learning transfer has been devised to highlight the relationship between learning transfer and skills training for today’s workplaces. The framework is a scientifically robust framework for transfer of learning at skill institutions. This study is significant in emphasizing the need for appropriate evaluation methods that can assist practitioners at skill institutions to develop learning transfer in a more credible manner.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.883
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.030
GPT teacher head0.309
Teacher spread0.279 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it